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An introduction to statistical learning : with Applications in Python / Gareth James ... [et al.]
| An introduction to statistical learning : with Applications in Python / Gareth James ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2023 |
| Descrizione fisica | xv, 60 p. : ill. ; 24 cm |
| Soggetto non controllato |
Data Mining
Inference Python Python software Statistical learning Supervised learning Unsupervsied learning |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0278708 |
| Cham, : Springer, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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An introduction to statistical learning : with Applications in Python / Gareth James ... [et al.]
| An introduction to statistical learning : with Applications in Python / Gareth James ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2023 |
| Descrizione fisica | xv, 60 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] 62J12 - Generalized linear models (logistic models) [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] |
| Soggetto non controllato |
Data Mining
Inference Python Python software Statistical learning Supervised learning Unsupervsied learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00278708 |
| Cham, : Springer, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
An introduction to statistics with Python : with applications in the life sciences / Thomas Haslwanter
| An introduction to statistics with Python : with applications in the life sciences / Thomas Haslwanter |
| Autore | Haslwanter, Thomas |
| Edizione | [2. ed] |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xvi, 336 p. : ill. ; 24 cm |
| Soggetto non controllato |
Alternative to R
Applications in the life sciences Bayesian Statistics Data Visualization Data analysis Generalized Linear Models Hypothesis tests Introductory Statistics Patterns in data Programming tools Python Python source code Regression Statistical Methods Statistical Modelling Statistical tests Survival times Time series |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0276849 |
Haslwanter, Thomas
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
An introduction to statistics with Python : with applications in the life sciences / Thomas Haslwanter
| An introduction to statistics with Python : with applications in the life sciences / Thomas Haslwanter |
| Autore | Haslwanter, Thomas |
| Edizione | [2. ed] |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xvi, 336 p. : ill. ; 24 cm |
| Soggetto non controllato |
Alternative to R
Applications in the life sciences Bayesian Statistics Data Visualization Data analysis Generalized Linear Models Hypothesis tests Introductory Statistics Patterns in data Programming tools Python Python source code Regression Statistical Methods Statistical Modelling Statistical tests Survival times Time series |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00276849 |
|
Haslwanter, Thomas
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||
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
An introduction to statistics with Python : with applications in the life sciences / Thomas Haslwanter
| An introduction to statistics with Python : with applications in the life sciences / Thomas Haslwanter |
| Autore | Haslwanter, Thomas |
| Pubbl/distr/stampa | [Cham], : Springer, 2016 |
| Descrizione fisica | XVII, 278 p. : ill. ; 24 cm |
| Soggetto topico |
92-XX - Biology and other natural sciences [MSC 2020]
62-XX - Statistics [MSC 2020] 62F15 - Bayesian inference [MSC 2020] 62F03 - Parametric hypothesis testing [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] 92B15 - General Biostatistics [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 62H15 - Hypothesis testing in multivariate analysis [MSC 2020] 62F40 - Bootstrap, jackknife and other resampling methods [MSC 2020] 62N02 - Estimation in survival analysis and censored data [MSC 2020] 62N03 - Testing in survival analysis and censored data [MSC 2020] 68T09 - Computational aspects of data analysis and big data [MSC 2020] |
| Soggetto non controllato |
Alternative to R
Applications in life sciences Data analysis Introductory Statistics Programming Python Python source code Statistical Methods Statistical tests Statistics and computing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0114408 |
|
Haslwanter, Thomas
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| [Cham], : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
An introduction to statistics with Python : with applications in the life sciences / Thomas Haslwanter
| An introduction to statistics with Python : with applications in the life sciences / Thomas Haslwanter |
| Autore | Haslwanter, Thomas |
| Pubbl/distr/stampa | [Cham], : Springer, 2016 |
| Descrizione fisica | XVII, 278 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62F03 - Parametric hypothesis testing [MSC 2020] 62F15 - Bayesian inference [MSC 2020] 62F40 - Bootstrap, jackknife and other resampling methods [MSC 2020] 62H15 - Hypothesis testing in multivariate analysis [MSC 2020] 62N02 - Estimation in survival analysis and censored data [MSC 2020] 62N03 - Testing in survival analysis and censored data [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 68T09 - Computational aspects of data analysis and big data [MSC 2020] 92-XX - Biology and other natural sciences [MSC 2020] 92B15 - General Biostatistics [MSC 2020] |
| Soggetto non controllato |
Alternative to R
Applications in life sciences Data analysis Introductory Statistics Programming Python Python source code Statistical Methods Statistical tests Statistics and computing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00114408 |
|
Haslwanter, Thomas
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| [Cham], : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Applied Time Series Analysis and Forecasting with Python / Changquan Huang, Alla Petukhina
| Applied Time Series Analysis and Forecasting with Python / Changquan Huang, Alla Petukhina |
| Autore | Huang, Changquan |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | x, 372 p. : ill. ; 24 cm |
| Altri autori (Persone) | Petukhina, Alla |
| Soggetto non controllato |
Artificial Intelligence
Big data analysis Data Visualization Data science Financial Time Series Forecasting Machine Learning for Time Series Markov switching models Multivariate time series Nonstationary Time Series Python State-space models Stationary Time Series Time Series Analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0276890 |
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Huang, Changquan
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Applied Time Series Analysis and Forecasting with Python / Changquan Huang, Alla Petukhina
| Applied Time Series Analysis and Forecasting with Python / Changquan Huang, Alla Petukhina |
| Autore | Huang, Changquan |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | x, 372 p. : ill. ; 24 cm |
| Altri autori (Persone) | Petukhina, Alla |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62M10 - Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Big data analysis Data Visualization Data science Financial Time Series Forecasting Machine Learning for Time Series Markov switching models Multivariate time series Nonstationary Time Series Python State-space models Stationary Time Series Time Series Analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00276890 |
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Huang, Changquan
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Bayesian Statistical Modeling with Stan, R, and Python / Kentaro Matsuura
| Bayesian Statistical Modeling with Stan, R, and Python / Kentaro Matsuura |
| Autore | Matsuura, Kentaro |
| Pubbl/distr/stampa | Singapore, : Springer, 2022 |
| Descrizione fisica | xix, 385 p. : ill. ; 24 cm |
| Soggetto non controllato |
Bayesian Modeling
Python Stan Statistical modeling |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0278348 |
|
Matsuura, Kentaro
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| Singapore, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Bayesian Statistical Modeling with Stan, R, and Python / Kentaro Matsuura
| Bayesian Statistical Modeling with Stan, R, and Python / Kentaro Matsuura |
| Autore | Matsuura, Kentaro |
| Pubbl/distr/stampa | Singapore, : Springer, 2022 |
| Descrizione fisica | xix, 385 p. : ill. ; 24 cm |
| Soggetto topico | 62-XX - Statistics [MSC 2020] |
| Soggetto non controllato |
Bayesian Modeling
Python Stan Statistical modeling |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00278348 |
|
Matsuura, Kentaro
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| Singapore, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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